Large Transmission Ratio Research Articles

Design of a storage mechanism designed for a railway vehicles producer

In this article the engineering design and strength analyses of a storage mechanism are presented. The handling device is intended to be placed in a warehouse and it will serve as a storage mechanism for longer metallurgical material in a railway vehicle manufacturing company. Stored material will be used for creation of some parts of railway wagons. It will allow to storage material in several levels in shelves. To meet requirements for manual control of the pull-out mechanism it will be necessary to design a pull-out mechanism with the sufficiently large transmission ratio in order to handle a shelf block weighing up to given load. Consequently, there are conducted the numeric strength analysis of steel construction which has to safely carry the total load of ten shelves.

Reliability Analysis of Filtering Reducers Considering Temperature Correction and Shock Load of Space

Owing to some excellent properties (such as large transmission ratio, high reliability, high precision, large stiffness, small volume and long service life), filtering reducers are suitable for occasions with high requirements (e.g. space equipment). However, the tough working condition in space (including frequent changes of temperature, and large temperature difference combined with shock loads) may significantly affect the reliability. In this paper, the expressions of the minimal and maximal instantaneous transmission ratios (ITRs) considering temperature correction are developed. The minimal and maximal ITRs from simulation are used to verify the accuracy. Moreover, the reliability of a filtering reducer under different temperatures and the shock load are calculated, respectively. The research is beneficial to the design of spacecraft mechanism.

Research of Planetary Gear Fault Diagnosis Based on Permutation Entropy of CEEMDAN and ANFIS.

For planetary gear has the characteristics of small volume, light weight and large transmission ratio, it is widely used in high speed and high power mechanical system. Poor working conditions result in frequent failures of planetary gear. A method is proposed for diagnosing faults in planetary gear based on permutation entropy of Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) Adaptive Neuro-fuzzy Inference System (ANFIS) in this paper. The original signal is decomposed into 6 intrinsic mode functions (IMF) and residual components by CEEMDAN. Since the IMF contains the main characteristic information of planetary gear faults, time complexity of IMFs are reflected by permutation entropies to quantify the fault features. The permutation entropies of each IMF component are defined as the input of ANFIS, and its parameters and membership functions are adaptively adjusted according to training samples. Finally, the fuzzy inference rules are determined, and the optimal ANFIS is obtained. The overall recognition rate of the test sample used for ANFIS is 90%, and the recognition rate of gear with one missing tooth is relatively high. The recognition rates of different fault gears based on the method can also achieve better results. Therefore, the proposed method can be applied to planetary gear fault diagnosis effectively.

Design principle and modeling method of asymmetric involute internal helical gears

In the field of mechanical engineering, involute helical gears are widely used. Compared with the involute spur gear, helical gears have a high bearing strength, more smooth transmission, less impact and less noise. The internal gear pairs have the features of large transmission ratio, low vibration, low noise and low wear and hence are widely used in planetary gear transmission systems. In order to meet the requirements of high strength, high speed of the modern gear transmission systems, a new type of asymmetric involute internal helical gears is designed based on conventional involute gears. This paper discusses the gear shaper cutter modeling for machining this new gear, analyzes the formation principle of asymmetric tooth profile and establishes a three-dimensional modeling by SolidWorks. Through MATLAB simulation, pressure angle, tooth number, coefficient of displacement and contact ratio of conventional and asymmetric gear are compared and analyzed. Using ANSYS, two types of gears are compared on strength in order to demonstrate superiority of asymmetric tooth and further study about the asymmetric internal helical gears.

One-way propagation of acoustic waves through a periodic structure

One-way acoustic transmission is achieved through a brass plate with a periodic grating on the surface. Using the Schlieren imaging technique, the positive and negative propagation processes of acoustic waves through the periodic structure were experimentally observed. Simulations were performed using the finite-element method. Both the experimental and simulation results revealed a very large transmission ratio between positive and negative incidence, thus demonstrating the feasibility of using this structure as an acoustic rectifier. The results indicate that the structure has a broadband working frequency. The structure has potential applications in ultrasonic medical devices and sonochemical reactors.

Design of a high-forward-transmission all-optical diode based on cascaded side-coupled photonic crystal cavities

A high-forward-transmission all-optical diode based on cascaded photonic crystal cavities is proposed. To obtain a high forward transmission and a large nonreciprocity, we generate a box-like spectrum by cascading two side-coupled photonic crystal cavities. We find that by appropriately adjusting the distance between two cavities, a high contrast of the transmission and a flat spectral lineshape with almost 100% transmission can be obtained. These characteristics are preferable for achieving a high forward transmission and a large nonreciprocity. Numerical results show that the designed all-optical diode performs perfect transmission with a large nonreciprocal transmission ratio of >50 dB.

Diagnosing planetary gear faults using the fuzzy entropy of LMD and ANFIS

The small size, low weight, and large transmission ratio of planetary gear have resulted in large-scale use, low speed, and heavy-duty mechanical systems. Poor working conditions of planetary gear lead to frequent occurrence of faults. A method is proposed for diagnosing faults in planetary gear based on fuzzy entropy of Local mean decomposition (LMD) and Adaptive neuro-fuzzy inference system (ANFIS). The original vibration signal is decomposed into six Product function (PF) components and a residual using LMD. Given that decomposed PF components contain the main fault feature information, fuzzy entropy is used to reflect the complexity and irregularity of each PF component. The fuzzy entropies of each PF component are defined as the input of the ANFIS model, and its parameters and membership functions are adaptively adjusted based on training samples. Finally, fuzzy inference rules are determined, and the optimal ANFIS model is obtained. Testing samples are used to verity the trained ANFIS model. The overall fault recognition rate reaches 88.8%, and the fault recognition rate for gear with wear reaches 96%. Therefore, the proposed method is effective at diagnosing planetary gear faults.

Study on planetary gear fault diagnosis based on entropy feature fusion of ensemble empirical mode decomposition

Because planetary gear is characterized by its small size, light weight and large transmission ratio, it is widely used in large-scale, low-speed and heavy-duty mechanical systems. Therefore, the fault diagnosis of planetary gear is a key to ensure the safe and reliable operation of such mechanical equipment. A fault diagnosis method of planetary gear based on the entropy feature fusion of ensemble empirical mode decomposition (EEMD) is proposed. The intrinsic mode functions (IMFs) with small modal aliasing are obtained by EEMD, and the original feature set is composed of various entropy features of each IMF. To address the insensitive features in the original feature set and the excessive feature dimension, kernel principal component analysis (KPCA) is used to process the original feature set. Kernel principal component extraction and feature dimension reduction are performed. The fault diagnosis of planetary gear is eventually realized by applying the extracted kernel principal components and learning vector quantization (LVQ) neural network. The experiments under different operation conditions are carried out, and the experimental results indicate that the proposed method is capable of extracting the sensitive features and recognizing the fault statuses. The overall recognition rate reaches to 96% when the motor output frequency is 45Hz and the load is 13.5Nm, and the fault recognition rates of the normal gear, the gear with one missing tooth and the broken gear can reach to 100%. The recognition rates of different fault gears under other operation conditions also can achieve better results. Thus, the proposed method is effective for the diagnosis of planetary gear faults.

Iterative generalized time–frequency reassignment for planetary gearbox fault diagnosis under nonstationary conditions

Planetary gearboxes are widely used in many sorts of machinery, for its large transmission ratio and high load bearing capacity in a compact structure. Their fault diagnosis relies on effective identification of fault characteristic frequencies. However, in addition to the vibration complexity caused by intricate mechanical kinematics, volatile external conditions result in time-varying running speed and/or load, and therefore nonstationary vibration signals. This usually leads to time-varying complex fault characteristics, and adds difficulty to planetary gearbox fault diagnosis. Time–frequency analysis is an effective approach to extracting the frequency components and their time variation of nonstationary signals. Nevertheless, the commonly used time–frequency analysis methods suffer from poor time–frequency resolution as well as outer and inner interferences, which hinder accurate identification of time-varying fault characteristic frequencies. Although time–frequency reassignment improves the time–frequency readability, it is essentially subject to the constraints of mono-component and symmetric time–frequency distribution about true instantaneous frequency. Hence, it is still susceptible to erroneous energy reallocation or even generates pseudo interferences, particularly for multi-component signals of highly nonlinear instantaneous frequency. In this paper, to overcome the limitations of time–frequency reassignment, we propose an improvement with fine time–frequency resolution and free from interferences for highly nonstationary multi-component signals, by exploiting the merits of iterative generalized demodulation. The signal is firstly decomposed into mono-components of constant frequency by iterative generalized demodulation. Time–frequency reassignment is then applied to each generalized demodulated mono-component, obtaining a fine time–frequency distribution. Finally, the time–frequency distribution of each signal component is restored and superposed to get the time–frequency distribution of original signal. The proposed method is validated using both numerical simulated and lab experimental planetary gearbox vibration signals. The time-varying gear fault symptoms are successfully extracted, showing effectiveness of the proposed iterative generalized time–frequency reassignment method in planetary gearbox fault diagnosis under nonstationary conditions.

Design of a reflection-suppressed all-optical diode based on asymmetric L-shaped nonlinear photonic crystal cavity

A simple design method for suppressing the reflection of the all-optical diode based on the L-shaped photonic crystal (PC) cavity is proposed. Analyzing the linear resonant characteristics of the PC cavity and using the nonlinear coupled-mode theory, the strategy for obtaining reflection-suppressed structure is illustrated. Based on the design rule, a “reflection-suppressed all-optical diode” is presented, and numerical solutions indicate that the designed structure has a small reflection as well as an extremely large nonreciprocal transmission ratio.

Research of weak fault feature information extraction of planetary gear based on ensemble empirical mode decomposition and adaptive stochastic resonance

Characterized by small size, light weight and large transmission ratio, planetary gear transmission is widely used in large scale complex mechanical system with low speed and heavy duty. However, due to the influences of operating condition, manufacturing error, assembly error and multi-tooth meshing, the vibration signal of planetary gear exhibits the characteristics of nonlinear and non-stationary. Especially when early gear fault occurs, the weak fault feature information is submerged in interfering signal. A weak fault feature information extraction method of planetary gear based on Ensemble Empirical Mode Decomposition (EEMD) and Adaptive Stochastic Resonance (ASR) is proposed. The original signal is decomposed to the Intrinsic Mode Functions (IMFs) with small modal aliasing by EEMD. The Signal to Noise Ratio (SNR) of fault feature frequency information of each IMF is calculated, and the IMFs with first four higher SNR are reconstructed and selected as the effective IMFs containing main fault feature information. ASR system is built by combining Particle Swarm Optimization (PSO) and Stochastic Resonance (SR). PSO algorithm is used to optimize the critical parameters of SR, and SNR of ASR output signal is defined as an optimization objective. When the signal reconstructed by effective IMFs is inputted into ASR system, the weak fault feature information can be extracted from the output signal of ASR system. The experimental results show that the proposed method can extract the weak fault feature information of normal gear and fault gears successfully. The amplitudes of fault feature frequency and its sidebands generated by planetary gear fault have a significantly increase, and the effects on sideband amplitudes of faults become even greater than that on the amplitude of fault feature frequency. For different gear faults, the amplitude of fault feature frequency has different changes, meanwhile different sidebands are produced. Planetary gear fault diagnosis can be achieved accurately by comparing the extracted weak fault feature information, so it is an effective method of weak fault feature information extraction of planetary gear.

Effect of drive mechanisms on dynamic characteristics of spacecraft tracking-drive flexible systems

Spacecraft tracking-drive flexible systems (STFS) consist of drive mechanisms and flexible structures, including solar array and a variety of large-scale antennas. The electromechanical interaction inside drive mechanisms makes it quite complicated to directly analyze the dynamic characteristics of an STFS. In this paper, an indirect dynamic characteristic analysis method for operating-state STFS is presented. The proposed method utilizes the structure dynamics approximation of drive mechanisms that converts the electromechanical model of an STFS into a structure dynamic model with elastic boundary conditions. The structure dynamics approximation and the dynamic characteristic analysis method are validated by experimental and analytical results, respectively. The analysis results indicate that the gear transmission ratio and viscous friction coefficient are the primary factors in approximating boundary stiffness and damping. Dynamic characteristics of an STFS with a large gear transmission ratio are close to that of a flexible structure with a cantilever boundary. Otherwise, torsion-mode natural frequencies of the STFS become smaller and corresponding modal damping ratios become larger, as a result of the local stiffness and damping features of drive mechanisms.

Worm and Worm Wheel Kinematics Simulation of a Rail Transport Based on ADAMS

Worm and worm gear is widely used in modern mechanical industry, it has a lot of advantages including large transmission ratio, compact structure, strong bearing capacity, stable transmission and self-locking performance etc. However, the kinematics characteristic is very important for the performance of equipment. So this article to the worm as the research object, which of the lifting mechanism in rail transport. First, making 3D modeling by Solid Edge V20, Then put the 3D model into the ADAMS, and start the kinematics simulation about transmission mechanism. This paper mainly simulates the angular velocity and angular acceleration of worm when its working, then comparing the change law of the motion curves, and analysis of the results. It can shorten design cycle, improve the design accuracy, reduce the cost of product development, and also create the conditions for the follow-up mechanism optimization and finite element analysis.

Application of Planetary Gear Transmission Technology in Tracked Combine Harvester

The tracked combine agricultural machinery is a most complex in structure, high technology content, the manufacture technology of very strict requirements of product. Our crawlers combine 1/3 of the fault from the walking gear system in operation. This paper adopts the planetary wheel transmission, because it has the advantages of compact structure, small volume, large transmission ratio, torque / volume ratio, high efficiency, and high reliability, meet the structure and characteristics of the combine harvester. This technology can save the transmission assembly, avoid the fault of gearbox assembly; improve the combine harvester of paddy field through. Keywords: Mechanical design;Combine Harvester;Planetary Gear;Transmission Technology

Study on ZI worm and helical gear drive with large transmission ratio

A ZI worm and helical gear drive is composed of an involute helicoid worm and a helical gear. Its application is limited due to less studies on the transmission performance with a large transmission ratio. In this paper, the design method of the drive is developed as: the parameters of the ZI worm should be the same as those of the helical gear; the helix angle β1 and the reference diameter factor d1∗ of the ZI worm should be greater than the minimum values proposed. The TCA of the drive shows that: the contact areas on the tooth surfaces are narrow; the effective face width of the ZI worm is larger than that of the helical gear; the contact ratio is less than 2; when the number of threads of the ZI worm changes from 1 to 5, the contact ratio decreases slightly, the effective face width of the worm decreases and that of the helical gear increases correspondingly. The instantaneous transmission ratio is proved theoretically to be constant and the assembly errors cause small shifts of the paths of contact.

Analysis on the Key Parameters of Aerospace Microminiaturization Decelerator

A high efficiency special transmission decelerator is designed by scheme design, structural design, optimization design, and return difference analysis and computer simulation. Small teeth difference transmission with the first level bevel gear pair and the second level beveloid gear pair is adopted as the form of transmission in the decelerating system. Great torque and big bending moment are available by transmission ratio formula deduction, force analysis and strength analysis. The particle swarm optimization and the genetic algorithm have been combined and the mutation operator optimization model has been proposed to optimize the design of decelerator. Then the transmission with large transmission ratio, high torque, high power and high precision will be realized in small space. This model has solved the problems of particle swarm optimization in mechanical design. For example, there are more variables, it is constrained and it is easily precocious. This model has provided the theoretical basis for the optimum design of microminiaturization gear system. DOI: http://dx.doi.org/10.11591/telkomnika.v11i10.3399

Tooth Profile Design for Translational Meshing Motor

As the reason for large transmission ratio, small center distance and interference on translational motor body, the design method of involute gear for translational meshing motor was proposed. In order to get appropriate tooth profile parameters, the trail calculation considering the conditions of interference and coincidence degree were applied using the tooth profile parameters calculated from given module, number of teeth, pressure angle and modification coefficient. The internal meshing gears was designed and processed based on proposed method. The novel translational meshing motor using designed involute gears operates successfully and efficiently which testify the validity and feasibility of proposed method.

Dynamic simulation of planetary gear with tooth root crack in ring gear

Planetary gear is widely used in different areas due to its advantages such as compactness, large torque-to-weight ratio, large transmission ratios, reduced noise and vibrations. However, the tooth faults like cracks are seldom concentrated. In this paper, a mesh stiffness model of internal gear pair with a tooth root crack in the ring gear is derived based on the potential energy principle. The mesh stiffness model is incorporated into the dynamic model of a one-stage planetary gear set with 21-degree-of-freedom (DOF) to investigate the effect of the internal gear tooth root crack. The crack cases with different dimensions are designed in this paper to demonstrate their influences on the mesh stiffness and the dynamic performance of the planetary gear set. The simulated results show that bigger reduction in mesh stiffness is caused by the growth in the crack size. And the impulsive vibrations and sidebands can be observed in the dynamic response of the planetary gear set in time and frequency domains, respectively. Both their amplitudes increase as the crack propagation which supply the possibility for them to be the indicators in the condition monitoring and fault diagnosis of planetary gear system.

Planetary gearbox fault diagnosis using an adaptive stochastic resonance method

Planetary gearboxes are widely used in aerospace, automotive and heavy industry applications due to their large transmission ratio, strong load-bearing capacity and high transmission efficiency. The tough operation conditions of heavy duty and intensive impact load may cause gear tooth damage such as fatigue crack and teeth missed etc. The challenging issues in fault diagnosis of planetary gearboxes include selection of sensitive measurement locations, investigation of vibration transmission paths and weak feature extraction. One of them is how to effectively discover the weak characteristics from noisy signals of faulty components in planetary gearboxes. To address the issue in fault diagnosis of planetary gearboxes, an adaptive stochastic resonance (ASR) method is proposed in this paper. The ASR method utilizes the optimization ability of ant colony algorithms and adaptively realizes the optimal stochastic resonance system matching input signals. Using the ASR method, the noise may be weakened and weak characteristics highlighted, and therefore the faults can be diagnosed accurately. A planetary gearbox test rig is established and experiments with sun gear faults including a chipped tooth and a missing tooth are conducted. And the vibration signals are collected under the loaded condition and various motor speeds. The proposed method is used to process the collected signals and the results of feature extraction and fault diagnosis demonstrate its effectiveness.

Fault detection of planetary gearboxes using new diagnostic parameters

Planetary gearboxes are commonly used in modern industry because of their large transmission ratio and strong load-bearing capacity. They generally work under heavy load and tough working environment and therefore their key components including sun gear, planet gears, ring gear, etc are subject to severe pitting and fatigue crack. Planetary gearboxes significantly differ from fixed-axis gearboxes and exhibit unique behavior, which invalidates the use of the diagnostic parameters developed and suitable for fixed-axis gearboxes. Therefore, there is a need to develop parameters specifically for detecting and diagnosing faults of planetary gearboxes. In this study, two diagnostic parameters are proposed based on the examination of the vibration characteristics of planetary gearboxes in both time and frequency domains. One is the root mean square of the filtered signal (FRMS) and the other is the normalized summation of positive amplitudes of the difference spectrum between the unknown signal and the healthy signal (NSDS). To test the proposed diagnostic parameters, we conducted experiments on a planetary gearbox test rig with sun gear faults including a cracked tooth and a pitted tooth. The vibration signals were measured under different motor speeds. The proposed parameters are compared with the existing parameters reported in the literature. The comparison results show the proposed diagnostic parameters perform better than others.